Changes in the vertical distribution of leaf area enhanced light interception efficiency in maize over generations of selection

Abstract

Breeders select for yield, thereby indirectly selecting for traits that contribute to it. We tested if breeding has affected a range of traits involved in plant architecture and light interception, via the analysis of a panel of 60 maize hybrids released from 1950 to 2015. This was based on novel traits calculated from reconstructions derived from a phenotyping platform. The contribution of these traits to light interception was assessed in virtual field canopies composed of 3D plant reconstructions, with a model tested in a real field. Two categories of traits had different contributions to genetic progress. (a) The vertical distribution of leaf area had a high heritability and showed a marked trend over generations of selection. Leaf area tended to be located at lower positions in the canopy, thereby improving light penetration and distribution in the canopy. This potentially increased the carbon availability to ears, via the amount of light absorbed by the intermediate canopy layer. (b) Neither the horizontal distribution of leaves in the relation to plant rows nor the response of light interception to plant density showed appreciable trends with generations. Hence, among many architectural traits, the vertical distribution of leaf area was the main indirect target of selection.

A new empirical equation to describe the vertical leaf distribution profile of maize

“…Water shortage limited elongation and expansion growth, moisture content and photosynthesis of leaves, which influences on the growth and development of maize plant (Duvick and Cassman, 1999;Zhang et al, 2019). The morphological changes are observed in maize hybrids released over different generations in American (Duvick and Cassman, 1999), European (Perez et al, 2019) and Chinese (Ma et al, 2014) projects. The number of leaves per plant increased and the leaf area index tend to be higher for modern hybrids than older ones.…”

Simulating the effect of flowering time on maize individual leaf area in contrasting environmental scenarios

“…(ii) A second possible use of this model is to simulate the consequences of plant architecture traits on light interception. We have recently shown that changes in distribution of leaf area along leaf ranks allowed a genetic progress of the amount of light intercepted by the canopy layer hosting maize ears ( Perez et al , 2019 ). Finally, the 10 genotype-dependent parameters of the model may be predicted via genomic prediction based on a set of platform experiments such as those in Dataset C, thereby allowing one to predict the leaf area of hundreds of genotypes from their genotypic markers in hundreds of fields, as recently carried out for flowering time ( Li et al , 2018 ) or for the responses of yield to environmental conditions ( Millet et al , 2019 ).…”

“…First, the final leaf number ( N final ) is closely related to the duration (number of plastochrons) from plant emergence to the floral transition of the shoot apex, but also to flowering time ( Parent et al , 2018 ). Hence, flowering time indirectly affects final leaf area, the vertical distribution of leaf area, and that of light interception ( Perez et al , 2019 ). Most models take these effects into account via the duration of leaf growth as a whole.…”

Efficient Execution of Scientific Workflows in the Cloud Through Adaptive Caching

“…In Figure 1.5, the same Binarize fragment is reused and the 3D reconstruction fragment is added to reconstruct the volume of the 1,680 plants in 3D. This SWf reuses the same Binarize segment to reconstruct the volume of the 1600 plants in 3D (3D reconstruction fragment) and compute the light intercepted by each plant placed in a virtual scene reproducing the canopy in the glasshouse ( [6,26]). Finally, in the SWf shown in Figure 1.6, the previous SWf is reused by Chen et al ( [8]), but with different parameters to study the environmental versus the genetic influence of biomass accumulation.…”